The principal focus of this work has been on developing novel gene mapping strategies that can be used to map biologically important traits that are refractory to conventional techniques. Many biological traits, such as disease susceptibilities, have underlying genetic components that are difficult to identify, let alone to map, by conventional means. For instance, disease-resistant genes segregating in a population will only be detectable in families whose members have been exposed to the causative agent. While such studies can be readily achieved in experimental animal models, the difficulty of collecting appropriate human families is sometimes formidable. As an alternative to conventional linkage analysis in human pedigrees, we have developed and implemented a population-based approach: mapping by admixture linkage disequilibrium (MALD). A second focus of this work is the synthesis and analysis of genetic maps. Gene mapping data is intrinsically graphical in that it represents localization of a gene either to an interval demarcated by some coordinates, often other loci, or to a point that is in some sense a "best estimate" of where the gene belongs. Such mapping data often require manipulation, both graphical and statistical. These efforts concentrate on the development of computer algorithms to logically synthesize and analyze these maps, including the facilitation of comparative mapping research.